Simultaneous tracking of division and differentiation from individual hematopoietic stem and progenitor cells reveals within-family homogeneity despite population heterogeneity

Abstract

The advent of high throughput single cell methods such as scRNA-seq has uncovered substantial heterogeneity in the pool of hematopoietic stem and progenitor cells (HSPCs). A significant issue is how to reconcile those findings with the standard model of hematopoietic development, and a fundamental question is how much instruction is inherited by offspring from their ancestors. To address this, we further developed a high-throughput method that enables simultaneously determination of common ancestor, generation, and differentiation status of a large collection of single cells. Data from it revealed that while there is substantial population-level heterogeneity, cells that derived from a common ancestor were highly concordant in their division progression and share similar differentiation outcomes, revealing significant familial effects on both division and differentiation. Although each family diversifies to some extent, the overall collection of cell types observed in a population is largely composed of homogeneous families from heterogeneous ancestors. Heterogeneity between families could be explained, in part, by differences in ancestral expression of cellsurface markers that are used for phenotypic HSPC identification: CD48, SCA-1, c-kit and Flt3. These data call for a revision of the fundamental model of haematopoiesis from a single tree to an ensemble of trees from distinct ancestors where common ancestor effect must be considered. As HSPCs are cultured in the clinic before bone marrow transplantation, our results suggest that the broad range of engraftment and proliferation capacities of HSPCs could be consequences of the heterogeneity in their engrafted families, and altered culture conditions might reduce heterogeneity between families, possibly improving transplantation outcomes.

Erythropoietin directly remodels the clonal composition of murine hematopoietic multipotent progenitor cells

“…ME-biased HSCs produced the majority of erythroid cells (57% +/-10%), MB-biased HSCs produced the majority of B-cells (58% +/-36%), and ME-and MB-biased HSCs contributed the majority of myeloid cells (MB-biased 45% +/-38% and ME-biased 20% +/-13%, together 65% +/-25%). To test the significance of this effect, we used a permutation test, which compares the effect size between control and EPO group to the one of all random groupings of mice 51 . The contributions of the ME-and of the MB-biased HSC classes to the different lineages were significantly different in EPO and control groups (Supplementary Table 1).…”

“…Significance of changes in barcoding results (e.g. changed contribution of barcode classes to lineages) were analyzed using a permutation test as in 51 . Briefly, by permuting all mice of control and EPO groups, the generated differences of all random groupings were compared to the observed difference between control and EPO group.…”

“…In brief, read counts of each barcode in the different cell lineages were normalized enabling categorization into classes of biased output toward the analyzed lineages using a threshold of 10% of barcode reads (Other thresholds in Supplementary Figure 3c). Statistics on barcoding results were performed using a permutation test as in 35 . Significance of flow cytometry results was assessed using Student's T test.…”

“…To test the significance of this effect, we used a permutation test, which compares the effect size between control and EPO group to the one of all random groupings of mice 35 . The contributions of the ME-and of the MB-biased HSPC classes to the different lineages were significantly different in EPO and control groups (Supplementary Table 1).…”

Erythropoietin directly remodels the clonal composition of murine hematopoietic multipotent progenitor cells

“…By permutating the mice of control and EPO groups, the random distribution of this output was generated and compared to the real output difference between control and EPO group. A pvalue was generated as in47…”